Regime change detection in irregularly sampled time series
Data Analysis, Statistics and Probability
2024-01-31 v1 Chaotic Dynamics
Atmospheric and Oceanic Physics
Abstract
Irregular sampling is a common problem in palaeoclimate studies. We propose a method that provides regularly sampled time series and at the same time a difference filtering of the data. The differences between successive time instances are derived by a transformation costs procedure. A subsequent recurrence analysis is used to investigate regime transitions. This approach is applied on speleothem based palaeoclimate proxy data from the Indonesian-Australian monsoon region. We can clearly identify Heinrich events in the palaeoclimate as characteristic changes in the dynamics.
Cite
@article{arxiv.2401.10006,
title = {Regime change detection in irregularly sampled time series},
author = {Norbert Marwan and Deniz Eroglu and Ibrahim Ozken and Thomas Stemler and Karl-Heinz Wyrwoll and Jürgen Kurths},
journal= {arXiv preprint arXiv:2401.10006},
year = {2024}
}
Comments
12 pages, 3 figures